Control Schemes of Switching Converters

2016 ◽  
pp. 125-134 ◽  
Author(s):  
Terukazu Sato
Author(s):  
Joseph Ayers

This chapter describes how synthetic biology and organic electronics can integrate neurobiology and robotics to form a basis for biohybrid robots and synthetic neuroethology. Biomimetic robots capture the performance advantages of animal models by mimicking the behavioral control schemes evolved in nature, based on modularized devices that capture the biomechanics and control principles of the nervous system. However, current robots are blind to chemical senses, difficult to miniaturize, and require chemical batteries. These obstacles can be overcome by integration of living engineered cells. Synthetic biology seeks to build devices and systems from fungible gene parts (gene systems coding different proteins) integrated into a chassis (induced pluripotent eukaryotic cells, yeast, or bacteria) to produce devices with properties not found in nature. Biohybrid robots are examples of such systems (interacting sets of devices). A nascent literature describes genes that can mediate organ levels of organization. Such capabilities, applied to biohybrid systems, portend truly biological robots guided, controlled, and actuated solely by life processes.


2014 ◽  
Vol 575 ◽  
pp. 805-808
Author(s):  
Jin Hong Zhu ◽  
Ze Guo Wei

In this paper, remote monitoring technology and its application to control of industrial power supply are discussed in detail, including its composition, function and classification. The two approaches of wired and wireless communication are analyzed, and four cases of typical systems are introduced as well. Practice has proved that the presented several control schemes are feasible and effective.


Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 651
Author(s):  
Wouter Schinkel ◽  
Tom van der Sande ◽  
Henk Nijmeijer

A cooperative state estimation framework for automated vehicle applications is presented and demonstrated via simulations, the estimation framework is used to estimate the state of a lead and following vehicle simultaneously. Recent developments in the field of cooperative driving require novel techniques to ensure accurate and stable vehicle following behavior. Control schemes for the cooperative control of longitudinal and lateral vehicle dynamics generally require vehicle state information about the lead vehicle, which in some cases cannot be accurately measured. Including vehicle-to-vehicle communication in the state estimation process can provide the required input signals for the practical implementation of cooperative control schemes. This study is focused on demonstrating the benefits of using vehicle-to-vehicle communication in the state estimation of a lead and following vehicle via simulations. The state estimator, which uses a cascaded Kalman filtering process, takes the operating frequencies of different sensors into account in the estimation process. Simulation results of three different driving scenarios demonstrate the benefits of using vehicle-to-vehicle communication as well as the attenuation of measurement noise. Furthermore, in contrast to relying on low frequency measurement data for the input signals of cooperative control schemes, the state estimator provides a state estimate at every sample.


Energies ◽  
2020 ◽  
Vol 14 (1) ◽  
pp. 55
Author(s):  
Nicholas Hawkins ◽  
Bhagyashri Bhagwat ◽  
Michael L. McIntyre

In this paper, a nonlinear controller is proposed to manage the rotational speed of a full-variable Squirrel Cage Induction Generator wind turbine. This control scheme improves upon tractional vector controllers by removing the need for a rotor flux observer. Additionally, the proposed controller manages the performance through turbulent wind conditions by accounting for unmeasurable wind torque dynamics. This model-based approach utilizes a current-based control in place of traditional voltage-mode control and is validated using a Lyapunov-based stability analysis. The proposed scheme is compared to a linear vector controller through simulation results. These results demonstrate that the proposed controller is far more robust to wind turbulence than traditional control schemes.


Processes ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 363
Author(s):  
Chii-Dong Ho ◽  
Yih-Hang Chen ◽  
Chao-Min Chang ◽  
Hsuan Chang

For the sour water strippers in petroleum refinery plants, three prediction models were developed first, including the estimators of sour water feed concentrations using convenient online measurements, the minimum reboiler duty and the corresponding internal temperature at a specific location (Tstage,29). Feedforward control schemes were developed based on these prediction models. Four categories of control schemes, including feedforward, feedback, feedback with external reset, and feedforward-feedback, were proposed and evaluated by the rigorous dynamic simulation model of the sour water stripper for their dynamic responses to the sour water feed stream disturbances. The comparison of control performance, in terms of the settling time, integrated absolute error (IAE) of the NH3 concentration of the stripped sour water and IAE of the specific reboiler duty, reveals that FFT (feedforward control of Tstage,29) and FBA-DT3 (feedback control with 3 min concentration measurement delay) are the best control schemes. The second-best control scheme is FBAT (cascade feedback control of concentration with temperature).


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